mmfewshot
mmselfsup
| mmfewshot | mmselfsup | |
|---|---|---|
| 2 | 5 | |
| 660 | 3,084 | |
| 1.8% | 0.7% | |
| 0.0 | 5.3 | |
| 8 months ago | 10 months ago | |
| Python | Python | |
| Apache License 2.0 | Apache License 2.0 |
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mmfewshot
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MMDeploy: Deploy All the Algorithms of OpenMMLab
MMFewShot: OpenMMLab fewshot learning toolbox and benchmark.
- A new member of OpenMMLab-MMFewShot!
mmselfsup
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MMDeploy: Deploy All the Algorithms of OpenMMLab
MMSelfSup: OpenMMLab self-supervised learning toolbox and benchmark.
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Does anyone know how a loss curve like this can happen? Details in comments
For some reason, the loss goes up shaply right at the start and slowly goes back down. I am self-supervised pretraining an image modeling with DenseCL using mmselfsup (https://github.com/open-mmlab/mmselfsup). This shape happened on the Coco-2017 dataset and my custom dataset. As you can see, it happens consistently for different runs. How could the loss increase so sharply and is it indicative of an issue with the training? The loss peaks before the first epoch is finished. Unfortunately, the library does not support validation.
- Defect Detection using RPI
- [D] State-of-the-Art for Self-Supervised (Pre-)Training of CNN architectures (e.g. ResNet)?
- Rebirth! OpenSelfSup is upgraded to MMSelfSup
What are some alternatives?
ORBIT-Dataset - The ORBIT dataset is a collection of videos of objects in clean and cluttered scenes recorded by people who are blind/low-vision on a mobile phone. The dataset is presented with a teachable object recognition benchmark task which aims to drive few-shot learning on challenging real-world data.
Unsupervised-Semantic-Segmentation - Unsupervised Semantic Segmentation by Contrasting Object Mask Proposals. [ICCV 2021]
mmrotate - OpenMMLab Rotated Object Detection Toolbox and Benchmark
anomalib - An anomaly detection library comprising state-of-the-art algorithms and features such as experiment management, hyper-parameter optimization, and edge inference.
mmpose - OpenMMLab Pose Estimation Toolbox and Benchmark.
calibrated-backprojection-network - PyTorch Implementation of Unsupervised Depth Completion with Calibrated Backprojection Layers (ORAL, ICCV 2021)
test - Measuring Massive Multitask Language Understanding | ICLR 2021
mmagic - OpenMMLab Multimodal Advanced, Generative, and Intelligent Creation Toolbox. Unlock the magic 🪄: Generative-AI (AIGC), easy-to-use APIs, awsome model zoo, diffusion models, for text-to-image generation, image/video restoration/enhancement, etc.
mmflow - OpenMMLab optical flow toolbox and benchmark
barlowtwins - Implementation of Barlow Twins paper
mmdeploy - OpenMMLab Model Deployment Framework
Revisiting-Contrastive-SSL - Revisiting Contrastive Methods for Unsupervised Learning of Visual Representations. [NeurIPS 2021]